Current quantum audio watermarking schemes prioritize robustness but often overlook critical security vulnerabilities, leaving systems exposed to impersonation and unauthorized use. To address this gap, we propose a dual-security mechanism that synergistically integrates joint verification and certification of watermarks, inspired by the paging seal principle. Our framework incorporates Quantum Error Correction (QEC) coding to enhance resilience against qubit errors and malicious tampering. Experimental results show improved performance: the watermark maintains high imperceptible with SNR> 46 dB under increased embedding rates, and achieves a 62.5% reduction in average BER compared to several state-of-the-art methods at a qubit error probability of 0.10. These results suggest that the proposed approach offers enhanced security and robustness, representing a promising direction for secure quantum audio watermarking.
Current quantum audio watermarking schemes prioritize robustness but often overlook critical security vulnerabilities, leaving systems exposed to impersonation and unauthorized use. To address this gap, we propose a dual-security mechanism that synergistically integrates joint verification and certification of watermarks, inspired by the paging seal principle. Our framework incorporates Quantum Error Correction (QEC) coding to enhance resilience against qubit errors and malicious tampering. Experimental results show improved performance: the watermark maintains high imperceptible with SNR> 46 dB under increased embedding rates, and achieves a 62.5% reduction in average BER compared to several state-of-the-art methods at a qubit error probability of 0.10. These results suggest that the proposed approach offers enhanced security and robustness, representing a promising direction for secure quantum audio watermarking.
Abstract. This paper presents an energy-aware quantum audio watermarking framework that exploits quantum signal transformations and clustering techniques to achieve robust and imperceptible watermark embedding. The proposed method integrates the Quantum Discrete Wavelet Transform (QDWT), Quantum Discrete Cosine Transform (QDCT), quantum k-means (Q-means) clustering, and a dynamic XOR-based embedding mechanism. The host audio signal is segmented into frames and analyzed in the quantum transform domain to extract joint time–frequency features. Based on the transform-domain energy characteristics and clustering outcomes, perceptually tolerant embedding regions are adaptively identified using predefined energy thresholds. Watermark insertion is performed through quantum-controlled XOR operations, where the embedding depth is dynamically selected according to the energy level of each audio segment. This energy-driven strategy ensures minimal perceptual distortion while enhancing robustness against signal processing attacks. Experimental evaluations demonstrate that the proposed method consistently outperforms conventional LSB-based watermarking schemes, achieving high transparency with signal-to-noise ratio (SNR) values exceeding 60 dB and strong robustness with bit error rates (BER) below 0.1 under various qubit-flip noise and zero-attack scenarios. These results confirm the effectiveness of the proposed framework in preserving audio quality while maintaining reliable watermark recovery.
With the rise of quantum computing and the limitations of traditional encryption methods, ensuring secure data transmission in IoT frameworks has become increasingly critical. This work presents a quantum-enhanced hybrid communication system that integrates adaptive audio techniques with quantum image processing. The proposed system operates in three main stages: first, text data is converted into binary format and encoded into quantum circuits using Qiskit; second, the quantum-encoded data is embedded into audio signals using an adaptive Least Significant Bit (LSB) technique; finally, the stego-audio’s robustness is evaluated under simulated IoT network conditions. Unlike conventional approaches, this method offers dual-layer security by combining dynamic audio embedding with quantum-based image representation, making it resistant to both quantum attacks and signal degradation. Experimental results demonstrate strong performance, with a Peak Signal-to-Noise Ratio (PSNR) ranging from 45 to 50 dB, a Bit Error Rate (BER) below 2%, and entropy values exceeding 7.5. These outcomes indicate the system’s effectiveness for secure, quantum-resilient communication in IoT environments with bandwidth and security constraints.
As one of essential multimedia in quantum networks, the copyright protection of quantum audio has gradually become an important issue in the domain of quantum information hiding in the decades. In this paper, an improved quantum watermarking algorithm based on quantum audio by using least significant qubit (LSQb) modification is proposed. Compared with the previous achievements, it can effectively improve the robustness and security of watermark for copyright protection of quantum audio. In the new algorithm, the least significant bites and the peripheral least significant bits of the amplitudes are modified in terms of their logical consistency and correlation to enhance watermark robustness of resisting various illegal attacks. Furthermore, the new algorithm can avoid the weak robustness defect of many previous algorithms that directly embedded the watermark into the least significant bits. In order to implement the new algorithm, some specific quantum circuits are designed to obtain better applicability and scalability for embedding and extracting watermark. Finally, the simulation results including the values of audio waveforms and signal to noise ratios (SNR) prove that the new algorithm has good transparency, robustness, and security.
Protecting the ownership of pictures and the integrity of copyright law is now of paramount importance with the explosion in digital content, especially content that is vulnerable to manipulation and distribution without the copyright owner's permission. This research work combines post-quantum cryptography, Artificial intelligence (AI) and quantum computing aspects to introduce ground breaking quantum intelligent and secure architecture for image watermarking. The proposed system is using quantum transform methods for inserting undetectable and tamper- proof quantum watermarks into digital images. AI models are then applied to the images for change detection and immediate verification of the authenticity of the watermark. Therefore, quantum key distribution (QKD), lattice-based post-quantum cryptography and other quantum safe encryption schemes are employed to cryptographically secure the metadata of watermark for good cryptographic security. This hybrid approach has been shown to enhance the security against both classical and quantum attacks. NFT authentication, secure cloud storage of pictures, and protection for copyright in digital media are examples of some potential applications. Simulation and experimental results show increased strength of the watermark, accuracy of message about unauthorized insertion of the watermark, and enhanced cryptographic security with respect to all other methods. The article demonstrates how AI can be aligned with quantum computing in order to secure audio-visual content in post-quantum cyber security.
Abstract Quantum image processing, which merges classical image processing techniques with quantum computing, provides exceptional storage capacity and unparalleled parallel computing power. In this study, we present a quantum color image watermarking scheme that employs quantum error correction codes to address issues such as pixel loss and image distortion during watermark embedding and extraction. By utilizing the least significant bit method to embed the color values of the watermark image into those of the carrier image, we improve the scheme’s robustness. We also address the error correction capabilities of channel coding for phase-flip errors and follow the majority principle, resulting in more accurate extraction of the watermark image’s color and enhancing the watermarking scheme’s reliability and integrity. Our experimental simulations demonstrate that the proposed watermarking scheme boasts high security, strong robustness, and excellent concealment.
The paper presents a novel hybrid quantum water-marking method designed to enhance the security and robustness of digital media protection. The proposed scheme integrates a two-step encryption process, achieving high security while pre-serving quality. Key features include classical LSB substitution, quantum chaos matrix, and an improved quantum representation, offering superior resistance to attacks. By combining spatial and transform domain encryption, the method overcomes vulner-abilities in singular value decomposition, enhancing robustness and peak signal-to-noise ratio (PSNR). Compared to the latest developments-such as sinusoidal-tent map, multi-scale pattern-based quantum text watermarking (MPQTW), maximum pixel difference, tri-way pixel, and NEQR with Quantum Majority Finder (QMF)-the proposed approach shows an average PSNR improvement of approximately 20 % and a significant reduction in Bit Error Rate (BER) by 15.41 %. Additionally, the method demonstrates strong resistance to various attack types with a correlation two-dimensional (Corr 2D) value near 1, such as 0.994 against salt and pepper noise attacks. These results highlight a significant advancement in quantum watermarking technology, balancing improved perceptual quality, security, and robustness.